Math Can’t Solve Gerrymandering
Researchers use powerful geometrical methods to try fixing unfair districts. That alone isn’t enough; we need to fight the values behind gerrymandering
Voters cast their ballots at a polling station inside the Adamsville Baptist Church in Goldsboro, North Carolina, US, on Tuesday, March 5, 2024. This year’s Super Tuesday primaries will put Donald Trump on the cusp of the Republican nomination and launch the longest general election battle in recent US history.
Allison Joyce/Bloomberg via Getty Images
On March 5, known as Super Tuesday, 15 U.S. states held primaries or caucuses to select the Republican and Democratic party’s candidates—not just for president but also for Congress—for November’s general election. Those states include North Carolina and Texas, which are gerrymandered to give the Republican Party an advantage in voting. This geographical salami slicing of congressional districts played a part in handing the House of Representatives to Republicans in the 2022 elections, and could do the same this year.
Gerrymandering, by definition, is the practice of deliberately designing voting districts to give a political party, racial group or both an advantage at the polls, an electoral connivance first named in a political cartoon from 1812. State governments redraw electoral districts every 10 years in response to new U.S. Census data. This process is complicated by partisanship in many states and by the nation’s history of racist disenfranchisement.
Following a 1986 Supreme Court recommendation, a number of researchers, including political scientists and mathematicians, have developed tools to identify gerrymandering where it exists now and to guide in the creation of new districts. These tools are very sophisticated, involving advanced geometry and often requiring powerful computers to assess the best possible districting.
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